Gender Classification Research on Web Forum Users’ Posting Behaviors and Posting Contents

DOI

10.2991/icibet-14.2014.54How to use a DOI?

Keywords

Gender difference, user internet behavior, text mining, text classification, web forum

Abstract

The rise of Web2.0 makes more and more people participate in the network to exchange their views and information. In order to investigate whether gender differences exist in internet behaviors, this paper examined users’ posting behaviors and language usages in network forum. This paper selected cars and stock forum message contents from a Chinese forum as research data. By hypothesis testing approach, this study confirms gender differences in posting behaviors. Text classification algorithms were used to investigate the differences existing in language usage between male and female users. Results showed that gender classification can be carried out by analyzing user’s review content. By comparing several classification results, the SVM was found to have the highest classification efficiency.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yue Chen
AU  - Lijuan Bai
PY  - 2014/02
DA  - 2014/02
TI  - Gender Classification Research on Web Forum Users’ Posting Behaviors and Posting Contents
BT  - Proceedings of the 2014 International Conference on Information, Business and Education Technology
PB  - Atlantis Press
SP  - 200
EP  - 203
SN  - 1951-6851
UR  - https://doi.org/10.2991/icibet-14.2014.54
DO  - 10.2991/icibet-14.2014.54
ID  - Chen2014/02
ER  -